Learning with AI Hub

Beta

This product is in a pre-release state and might change or have limited support.
For more information, see the product launch
stages.

The collection of assets on AI Hub includes resources that you can use
to develop your understanding of machine learning (ML) concepts, technologies,
and infrastructure. If you are new to artificial intelligence (AI) and ML, the
Machine Learning Crash Course provides the
necessary foundation to get started using the ML assets on
AI Hub.

Here is an overview of some of the ways you can learn from the assets on
AI Hub:

Kubeflow pipelines: Kubeflow pipelines are
end-to-end machine learning (ML) workflows based on containers. You can
learn best practices for building complex ML workflows by studying the
implementation of the reference
pipelines on
AI Hub.

Services: The collection of services on AI Hub includes
APIs, building blocks, ML services, and infrastructure for training and
prediction. By investigating the services on
AI Hub, you can learn
about APIs, ML services, and infrastructure that you can use in you ML
system.

Technical guides: The technical guides on AI Hub
demonstrate how to implement complex AI use cases. These guides combine
services, infrastructure, and custom code to implement complete solutions.
By following the technical guides on
AI Hub, you
learn best practices that you can leverage when designing an AI system.